As mentioned previously it
is important to get business information in to the CMIS to enable us to perform
some correlations.
In the example below we
have taken business data and taken component data and we can now report on this
together to see if there is some kind of correlation.
In this example we can see that the number
of customer transactions (shown in dark blue) reasonably correlates with the
amount of CPU utilization.
Can we make some kind of
judgment based on just what we see here? Do we need to perform some further
statistical analysis on this data? What is the correlation co-efficiency for
our application data against the CPU utilization?
Closer to the value of 1
indicates that there is a very close correlation between the application data
and the underlying component data.
What can we do with
this information back to the business?
An example would be: This graph
indicates that there is a very close correlation between the number of customer
transactions and the CPU utilization. Therefore, if we plan on increasing the
number of customer transactions in the future we are likely to need to do a CPU
upgrade to cope with that demand.
On Friday I'll take a look at
some analytical modeling examples, based on forecasts given to us by
the business and how we can use modeling to show the business the likely impact of forthcoming initiatives.
Charles Johnson
Principal Consultant
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